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Staff Software Engineer, Google Cloud, Applied AI, Automotive AI Agent
GoogleSingaporeSenior8+ years
Apply Minimum qualifications:
- Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.
- 8 years of experience in software development and working with algorithms.
- 5 years of experience with software development in one or more general-purpose programming languages (e.g., Python, C++).
- Experience building and maintaining distributed systems, cloud APIs, and mobile or embedded software development kits (SDKs).
- Experience with AI/ML technologies, Large Language Models (LLMs) or Natural Language Understanding (NLU).
Preferred qualifications:
- Experience in productizing and productionalizing applied ML/NLP systems.
- Familiar with LLM technologies and experience in production-grade LLM-based applications.
- Ability to optimize systems end-to-end, ensuring safety and quality in a safety-critical automotive environment.
- Passion for innovations and converting new technologies (like "Live Mode" or Agentic workflows) into tangible product value.
About the job
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
Join the Automotive team as we are building the leading development platform for the AI-defined vehicle. We provide automotive original equipment manufacturer (OEMs) with a Gemini-native platform to build, deploy, and maintain intelligent agents. By adding vehicle integration with Gemini’s reasoning, we empower automakers to deliver proactive and personalized experiences that connect the driver's life inside and outside the car.
In this role, you will help us define the future of in-car interaction, ensuring our solutions are fully functional, localized for and scalable across customers, domains and various locations.
The Cloud Applied AI (AAI) powers business growth with Gemini Enterprise. Our portfolio includes Gemini Enterprise for Customer Experience (Shopping Agent, CX Agent Studio, Agent Assist, Vertex AI Search - Commerce, Customer Experience Insights), along with other vertical and domain packaged solutions. We enable high adoption and speed to value by building solutions that are quickly deployed, delivering new 0-to-1 capabilities with startup agility. Team members operate at the forefront of AI, collaborating directly with model builders with unprecedented speed. Join us to work on cutting-edge projects and shape the future of AI in a fast-paced, collaborative, and impactful environment.
Responsibilities
- Design, develop, and maintain scalable and reliable server-side infrastructure for the automotive AI agent platform using C++ and Go.
- Build and evolve one platform APIs, managing their lifecycle from experimental to general availability, ensuring they meet Google Cloud standards.
- Implement and integrate Google Cloud technologies and best practices, including control plane framework engine (CCFE), and ensure compliance with security and privacy horizontals (e.g., access transparency (AxT), customer-managed encryption keys (CMEK), virtual private cloud service controls (VPC-SC), data residency zones (DRZ)).
- Contribute to the design and implementation of backend systems supporting platform features, including potential monetization mechanisms.
- Write well-tested, production-ready code and participate in on-call rotations to support service reliability.
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